Fake Data Generator

The EasyFileKit Fake Data Generator creates realistic test records entirely in your browser. Pick from 18 field types including names, emails, phone numbers, addresses, company names, job titles, UUIDs, dates, booleans and numbers. Choose your output format — JSON, CSV or SQL INSERT statements — and download or copy the result in one click. No server, no API keys, no upload required.

Every developer needs sample data at some point: seeding a local database, building a UI prototype, writing integration tests or demoing a feature to stakeholders. Hardcoding records is tedious and unrealistic. Manually typing rows is slow and error-prone. A dedicated generator gives you hundreds of consistent, varied rows in seconds, so you can focus on the code that matters.

Without realistic test data, you cannot verify that your application handles edge cases correctly — unusually long names, special characters in email addresses, missing optional fields or boundary values in numeric fields. The generator produces varied enough data to surface these issues before they reach production, catching bugs that unit tests with static fixtures would miss.

| Field | Example Output |

| --- | --- |

| id | `a1b2c3d4-e5f6-7890-abcd-ef1234567890` |

| firstName | `Samantha` |

| lastName | `Nakamura` |

| email | `samantha.nakamura@example.com` |

| phone | `(415) 555-0198` |

| address | `742 Evergreen Terrace, Springfield` |

| city | `Austin` |

| state | `TX` |

| zip | `78701` |

| country | `US` |

| company | `Nakamura Consulting` |

| jobTitle | `Senior Product Designer` |

| age | `34` |

| date | `2024-03-15` |

| boolean | `true` |

| number | `42.7` |

| uuid | `f47ac10b-58cc-4372-a567-0e02b2c3d479` |

| lorem | `Lorem ipsum dolor sit amet...` |

Pick the fields you need — check the boxes next to each column type

Set the row count between 1 and 500 using the number input

Choose your output format: JSON array, comma-separated CSV or SQL INSERT statements

Click Generate and copy or download the result instantly

Tip: For database seeding, SQL INSERT format includes proper string escaping and wraps values in single quotes, ready to paste into a SQL client.

JSON mode produces a single array of objects with 2-space indentation — strings for names, numbers for ages, booleans for the boolean field. CSV mode generates a header row followed by data rows, with commas automatically escaped in strings. SQL mode wraps every row in an INSERT INTO statement with a default table name of `records`, with proper string escaping. All three formats are available with one click, and you can switch between them without regenerating the data.

Tip: For database seeding, SQL INSERT format is ready to paste into MySQL, PostgreSQL or SQLite. Rename the table and columns to match your schema.

The JSON output is particularly useful for frontend development — paste it directly into your state management mock data or use it as fixture files in your test suite. The CSV output works with any spreadsheet application or pandas DataFrame. The SQL output can be saved as a `.sql` file and run against your local development database in a single command.

First names, last names, cities, companies and job titles come from built-in arrays of real-world English-language values. IDs, ages and floating-point numbers use `crypto.getRandomValues` for cryptographic-quality randomness. Dates are generated within a configurable range. The combination produces data that looks realistic at a glance while being entirely synthetic. Every computation runs inside your browser — no data is uploaded, no cookies are set and no analytics track what you generate. You can even disconnect from the internet after the page loads and it will continue working.

Seeding a local development database with hundreds of user-like rows for integration testing

Building prototype dashboards and admin panels with realistic customer data before connecting a backend

Writing unit or integration tests that need varied input across multiple data types

Demonstrating a feature to stakeholders without exposing real user records or violating privacy policies

Generating sample payloads for API documentation and SDK examples

Populating a demo environment with plausible-looking records for sales demos or investor presentations

Q: Where does the random data come from?

A: Built-in arrays of first names, last names, cities, companies and jobs — combined with `crypto.getRandomValues` for IDs, ages and numbers.

Q: Is the data realistic?

A: Reasonably — names are real first and last names from common English-speaking countries, emails follow standard patterns, addresses use real city names. The data is fake and should not be used to impersonate anyone.

Q: Can I get the output as SQL?

A: Yes — SQL INSERT statements with proper string escaping. Useful for seeding test databases.

Q: Is the data uploaded anywhere?

A: No. Generation happens entirely in your browser. No server calls are made.

Random Number Generator — generate random integers or floats in any range

Username Generator — create unique usernames from names and patterns

UUID Generator — generate v4 UUIDs one or many at a time

CSV to JSON Converter — convert your generated CSV back to JSON if needed

Tool page — open the Fake Data Generator